Drawing on the dual process theory, this study investigates the impacts of systematic and heuristic cues on travelers’ cognitive trust, emotional trust, and adoption intention toward artificial intelligence (AI)–based recommendation systems in travel planning. The moderating effect of perceived risk is also examined. Two studies with both scenario-based surveys and lab experiment approaches are conducted. Findings suggest that while travelers utilize both systematic and heuristic cues, effects of systematic cues on adoption as a decision aid is stronger than the effects of heuristic cues. Emotional trust has a stronger impact on intention to adopt as a delegated agent than cognitive trust. Perceived risk moderates the relationships between systematic and heuristic cues, trust, and adoption intentions. When travelers perceive high risk, they rely more on systematic cues through building cognitive trust. However, when the level of perceived risk is low, travelers depend more on heuristic cues through establishing emotional trust.
AdamI.2015. “Backpackers’ Risk Perceptions and Risk Reduction Strategies in Ghana.” Tourism Management49:99–108.
2.
AgagG. M.El-MasryA. A.2017. “Why Do Consumers Trust Online Travel Websites? Drivers and Outcomes of Consumer Trust toward Online Travel Websites.” Journal of Travel Research56 (3): 347–69.
3.
AiJ.ChiO. H.OuyangZ.2019. “Categorizing Peer-to-Peer Review Site Features and Examining Their Impacts on Room Sales.” Journal of Hospitality Marketing & Management28 (7): 862–81.
4.
AnthesG.2017. “Artificial Intelligence Poised to Ride a New Wave: Flush with Recent Successes, and Pushed by Even Newer Technology, AI Systems Could Get Much Smarter.” Communications of the ACM60 (7): 19–21.
5.
BélangerF.CarterL.2008. “Trust and Risk in E-government Adoption.” Journal of Strategic Information Systems17 (2): 165–76.
6.
BhattacherjeeA.SanfordC.2006. “Influence Processes for Information Technology Acceptance: An Elaboration Likelihood Model.” MIS Quarterly30 (4): 805–25.
7.
BohnerG.ChaikenS.HunyadiP.1994. “The Role of Mood and Message Ambiguity in the Interplay of Heuristic and Systematic Processing.” European Journal of Social Psychology24 (1): 207–21.
8.
BohnerG.MoskowitzG. B.ChaikenS.1995. “The Interplay of Heuristic and Systematic Processing of Social Information.” European Review of Social Psychology6 (1): 33–68.
9.
BollenK.1989. Structural Equations with Latent Variables. New York: John Wiley.
10.
BruwerJ.CohenJ.2019. “Restaurants and Wine by-the-Glass Consumption: Motivational Process Model of Risk Perception, Involvement and Information-Related Behaviour.” International Journal of Hospitality Management77:270–80.
11.
CampbellM. C.GoodsteinR. C.2001. “The Moderating Effect of Perceived Risk on Consumers’ Evaluations of Product Incongruity: Preference for the Norm.” Journal of Consumer Research28 (3): 439–49.
12.
ChaikenS.1980. “Heuristic versus Systematic Information Processing and the Use of Source Message.” Journal of Personality & Social Psychology39 (5): 752–66.
13.
ChaikenS.LibermanA.EaglyA. H.1989. “Heuristic and Systematic Information Processing within and Beyond the Persuasion Context.” In Unintended Thought, edited by UlemanJ. S.BarghJ. A., 212. New York: Guilford.
14.
ChaikenS.MaheswaranD.1994. “Heuristic Processing Can Bias Systematic Processing: Effects of Source Credibility, Argument Ambiguity, and Task Importance on Attitude Judgment.” Journal of Personality and Social Psychology66 (3): 460–73.
15.
CharalambousG.FletcherS.WebbP.2015. “The Development of a Scale to Evaluate Trust in Industrial Human-Robot Collaboration.” International Journal of Social Robotics8 (2): 193–209.
16.
ChenS.ChaikenS.1999. “The Heuristic-Systematic Model in Its Broader Context.” In Dual-Process Theories in Social Psychology, edited by ChaikenS.TropeY., 73–96. New York: Guilford.
17.
CheungC. M. K.XiaoB. S.LiuI. L. B.2014. “Do Actions Speak Louder Than Voices? The Signaling Role of Social Information Cues in Influencing Consumer Purchase Decisions.” Decision Support Systems65:50–58.
18.
ChinW. W.MarcoulidesG.1998. “The Partial Least Squares Approach to Structural Equation Modeling.” In Modern Methods for Business Research, Chap 10, edited by MarcoulidesG. A.295–336. Mahwah, NJ: Lawrence Erlbaum.
19.
ChoiS.LiuS. Q.MattilaA. S.2019. “‘How May I Help You?’ Says a Robot: Examining Language Styles in the Service Encounter.” International Journal of Hospitality Management82:32–38.
DholakiaU. M.2001. “A Motivational Process Model of Product Involvement and Consumer Risk Perception.” European Journal of Marketing35 (11/12): 1340–62.
22.
DowellD.MorrisonM.HeffernanT.2015. “The Changing Importance of Affective Trust and Cognitive Trust across the Relationship Lifecycle: A Study of Business-to-Business Relationships.” Industrial Marketing Management44:119–30.
23.
DowlingG. R.1999. “Perceived Risk.” In The Elgar Companion to Consumer Research and Economic Psychology, edited by EarlPeter E.KempSimon, 419–24. Cheltenham, UK: Edward Elgar.
24.
DuanY.EdwardsJ. S.DwivediY. K.2019. “Artificial Intelligence for Decision Making in the Era of Big Data—Evolution, Challenges and Research Agenda.” International Journal of Information Management48:63–71.
25.
EaglyA. H.ChaikenS.1993. The Psychology of Attitudes. Fort Worth, TX: Harcourt Brace Jovanovich College.
26.
FalkR.MillerN.1992. A Primer for Soft Modeling. Akron, OH: University of Akron Press.
27.
FanA.WuL.MiaoL.MattilaA. S.2020. “When Does Technology Anthropomorphism Help Alleviate Customer Dissatisfaction after a Service Failure? The Moderating Role of Consumer Technology Self-Efficacy and Interdependent Self-Construal.” Journal of Hospitality Marketing & Management29 (3): 269–90.
28.
FeathermanM. S.PavlouP. A.2003. “Predicting E-services Adoption: A Perceived Risk Facets Perspective.” International Journal of Human-Computer Studies59 (4): 451–74.
29.
FerranC.WattsS.2008. “Videoconferencing in the Field: A Heuristic Processing Model.” Management Science54 (9): 1565–78.
30.
FornellC.BooksteinF. L.1982. “Two Structural Equation Models: Lisrel and Pls Applied to Consumer Exit-Voice Theory.” Journal of Marketing Research19 (4): 440–52.
31.
FotisJ.BuhalisD.RossidesN.2011. “Social Media Impact on Holiday Travel Planning: The Case of the Russian and the Fsu Markets.” International Journal of Online Marketing1 (4): 79–90.
32.
GaudielloI.ZibettiE.LefortS.ChetouaniM.IvaldiS.2016. “Trust as Indicator of Robot Functional and Social Acceptance. An Experimental Study on User Conformation to Icub Answers.” Computers in Human Behavior61:633–55.
33.
GefenD.2000. “E-commerce: The Role of Familiarity and Trust.” Omega28 (6): 725–37.
34.
GesslA. S.SchlöglS.MevenkampN.2019. “On the Perceptions and Acceptance of Artificially Intelligent Robotics and the Psychology of the Future Elderly.” Behaviour & Information Technology38 (11): 1068–87.
35.
GoudeyA.BonninG.2016. “Must Smart Objects Look Human? Study of the Impact of Anthropomorphism on the Acceptance of Companion Robots.” Recherche et Applications en Marketing (English Edition)31 (2): 2–20.
36.
GursoyD.2019. “A Critical Review of Determinants of Information Search Behavior and Utilization of Online Reviews in Decision Making Process.” International Journal of Hospitality Management76:53–60.
37.
GursoyD.ChiO. H.LuL.NunkooR.2019. “Consumers Acceptance of Artificially Intelligent (AI) Device Use in Service Delivery.” International Journal of Information Management49:157–69.
38.
GursoyD.YolalM.RibeiroM. A.NettoA. P.2016. “Impact of Trust on Local Residents’ Mega-event Perceptions and Their Support.” Journal of Travel Research56 (3): 393–406.
39.
HöpkenW.EberleT.FuchsM.LexhagenM.2020. “Improving Tourist Arrival Prediction: A Big Data and Artificial Neural Network Approach.” Journal of Travel Research. Published online June 11. doi:10.1177/0047287520921244.
40.
HancockP. A.BillingsD. R.SchaeferK. E.ChenJ. Y. C.de VisserE. J.ParasuramanR.2011. “A Meta-analysis of Factors Affecting Trust in Human-Robot Interaction.” Human Factors53 (5): 517–27.
41.
HarterJ. K.SchmidtF. L.HayesT. L.2002. “Business-Unit-Level Relationship between Employee Satisfaction, Employee Engagement, and Business Outcomes: A Meta-analysis.” Journal of Applied Psychology87 (2): 268–79.
42.
HenselerJ.RingleC.SinkovicsR.2009. “The Use of Partial Least Squares Path Modeling in International Marketing.” Advances in International Marketing20:277–319.
43.
HexmoorH.RahimiS.ChandranR.2008. “Delegations Guided by Trust and Autonomy.” Web Intelligence & Agent Systems6 (2): 137–55.
44.
HleeS.LeeH.KooC.2018. “Hospitality and Tourism Online Review Research: A Systematic Analysis and Heuristic-Systematic Model.” Sustainability10 (4): 1141.
45.
HongJ. J.DesaiK. K.2020. “Variety-Seeking Behavior and Information Processing in Choosing a Vacation Destination.” Journal of Travel Research59 (5): 850–63.
46.
HuangYu-ChihChangLan LanYuChia-PinChenJoseph. 2019. “Examining an Extended Technology Acceptance Model with Experience Construct on Hotel Consumers’ Adoption of Mobile Applications.” Journal of Hospitality Marketing & Management28 (8): 957–80.
47.
HurK.KimT. T.KaratepeO. M.LeeG.2017. “An Exploration of the Factors Influencing Social Media Continuance Usage and Information Sharing Intentions among Korean Travellers.” Tourism Management63:170–78.
48.
JunS. H.VogtC.2013. “Travel Information Processing Applying a Dual-Process Model.” Annals of Tourism Research40:191–212.
49.
KahnemanD.2003. “A Perspective on Judgment and Choice: Mapping Bounded Rationality.” American Psychologist58 (9): 697–720.
50.
KimH.-Y.McGillA. L.2018. “Minions for the Rich? Financial Status Changes How Consumers See Products with Anthropomorphic Features.” Journal of Consumer Research45 (2): 429–50.
51.
KimM.KimJ.2020. “The Influence of Authenticity of Online Reviews on Trust Formation among Travelers.” Journal of Travel Research59 (5): 763–76.
52.
KimM. J.PetrickJ. F.2020. “The Effect of Herding Behaviors on Dual-Route Processing of Communications Aimed at Tourism Crowdfunding Ventures.” Journal of Travel Research. Published online May21. doi:10.1177/0047287520919515.
53.
KlepperS.NaginD.1989. “The Deterrent Effect of Perceived Certainty and Severity of Punishment Revisited.” Criminology27 (4): 721–46.
54.
KomiakS. X.BenbasatI.2004. “Understanding Customer Trust in Agent-Mediated Electronic Commerce, Web-Mediated Electronic Commerce, and Traditional Commerce.” Information Technology and Management5 (1): 181–207.
55.
KomiakS. Y. X.BenbasatI.2006. “The Effects of Personalization and Familiarity on Trust and Adoption of Recommendation Agents.” MIS Quarterly30 (4): 941–60.
56.
KuoY.-F.WuC.-M.2012. “Satisfaction and Post-purchase Intentions with Service Recovery of Online Shopping Websites: Perspectives on Perceived Justice and Emotions.” International Journal of Information Management32 (2): 127–38.
57.
LawR.LiG.FongD. K. C.HanX.2019. “Tourism Demand Forecasting: A Deep Learning Approach.” Annals of Tourism Research75:410–23.
58.
LeungW. K. S.ShiS.ChowW. S.2020. “Impacts of User Interactions on Trust Development in C2C Social Commerce: The Central Role of Reciprocity.” Internet Research30 (1): 335–56.
59.
LewisJ. D.WeigertA.1985. “Trust as a Social Reality.” Social Forces63 (4): 967–85.
60.
Liébana-CabanillasF.Sánchez-FernándezJ.Muñoz-LeivaF.2014. “Antecedents of the Adoption of the New Mobile Payment Systems: The Moderating Effect of Age.” Computers in Human Behavior35:464–78.
61.
LiJ.BonnM. A.YeB. H.2019. “Hotel Employee’s Artificial Intelligence and Robotics Awareness and Its Impact on Turnover Intention: The Moderating Roles of Perceived Organizational Support and Competitive Psychological Climate.” Tourism Management73:172–81.
62.
LiangH.SarafN.HuQ.YajiongX.2007. “Assimilation of Enterprise Systems: The Effect of Institutional Pressures and the Mediating Role of Top Management.” MIS Quarterly31 (1): 59–87.
63.
LiaoZ.ZhengW.2018. “Using a Heuristic Algorithm to Design a Personalized Day Tour Route in a Time-Dependent Stochastic Environment.” Tourism Management68:284–300.
64.
LinH.ChiO. H.GursoyD.2020. “Antecedents of Customers’ Acceptance of Artificially Intelligent Robotic Device Use in Hospitality Services.” Journal of Hospitality Marketing & Management29 (5): 530–49.
65.
LuL.CaiR.GursoyD.2019. “Developing and Validating a Service Robot Integration Willingness Scale.” International Journal of Hospitality Management80:36–51.
66.
Luna-CortésG.López-BonillaJ. M.López-BonillaL. M.2019. “Self-Congruity, Social Value, and the Use of Virtual Social Networks by Generation Y Travelers.” Journal of Travel Research58 (3): 398–410.
67.
LuoX.LiH.ZhangJ.ShimJ. P.2010. “Examining Multi-Dimensional Trust and Multi-Faceted Risk in Initial Acceptance of Emerging Technologies: An Empirical Study of Mobile Banking Services.” Decision Support Systems49 (2): 222–34.
68.
MaesP.GuttmanR. H.MoukasA. G.1999. “Agents That Buy and Sell.” Communications of the ACM42 (3): 81–91.
69.
MarlerJ. H.FisherS. L.KeW.2009. “Employee Self-Service Technology Acceptance: A Comparison of Pre-Implementation and Post-Implementation Relationships.” Personnel Psychology62 (2): 327–58.
70.
McKnightD. H.ChoudhuryV.KacmarC.2002. “Developing and Validating Trust Measures for E-commerce: An Integrative Typology.” Information Systems Research13 (3): 334–59.
71.
MurphyJ.GretzelU.PesonenJ.2019. “Marketing Robot Services in Hospitality and Tourism: The Role of Anthropomorphism.” Journal of Travel & Tourism Marketing36 (7): 784–95.
72.
MurthiB. P. S.SarkarS.2003. “The Role of the Management Sciences in Research on Personalization.” Management Science49 (10): 1344–62.
73.
ParkJ.-Y.JangS.2013. “Confused by Too Many Choices? Choice Overload in Tourism.” Tourism Management35:1–12.
74.
ParkS.Tussyadiahl. P.2017. “Multidimensional Facets of Perceived Risk in Mobile Travel Booking.” Journal of Travel Research56 (7): 854–67.
75.
ParkS.Tussyadiahl. P.2019. “How Guests Develop Trust in Hosts: An Investigation of Trust Formation in P2P Accommodation.” Journal of Travel Research59 (8): 1402–12.
76.
PetterS.StraubD.RaiA.2007. “Specifying Formative Constructs in Information Systems Research.” MIS Quarterly31 (4): 623–56.
RohamM.GabrielyanA. R.ArcherN. P.2012. “Predicting the Impact of Hospital Health Information Technology Adoption on Patient Satisfaction.” Artificial Intelligence in Medicine56 (2): 123–35.
80.
SawyP. A. P. O. A. E.2006. “From IT Leveraging Competence to Competitive Advantage in Turbulent Environments: The Case of New Product Development.” Information Systems Research17 (3): 198–227.
81.
SchneiderS.LeyerM.2019. “Me or Information Technology? Adoption of Artificial Intelligence in the Delegation of Personal Strategic Decisions.” Managerial and Decision Economics40 (3): 223–31.
82.
SeegebarthB.BackhausC.WoisetschlägerD. M.2019. “The Role of Emotions in Shaping Purchase Intentions for Innovations Using Emerging Technologies: A Scenario-Based Investigation in the Context of Nanotechnology.” Psychology & Marketing36 (9): 844–62.
83.
SharifpourM.WaltersG.RitchieB. W.WinterC.2014. “Investigating the Role of Prior Knowledge in Tourist Decision Making: A Structural Equation Model of Risk Perceptions and Information Search.” Journal of Travel Research53 (3): 307–22.
84.
ShiS.ChowW. S.2015. “Trust Development and Transfer in Social Commerce: Prior Experience as Moderator.” Industrial Management & Data Systems115 (7): 1182–203.
85.
ShiS.GursoyD.ChenL.2019. “Conceptualizing Home-Sharing Lodging Experience and Its Impact on Destination Image Perception: A Mixed Method Approach.” Tourism Management75:245–56.
86.
SiponenM.VanceA.2010. “Neutralization: New Insights into the Problem of Employee Information Systems Security Policy Violations.” MIS Quarterly34 (3): 487–502.
87.
SouffriauW.VansteenwegenP.Vanden BergheG.Van OudheusdenD.2011. “The Planning of Cycle Trips in the Province of East Flanders.” Omega39 (2): 209–13.
88.
SparksB. A.PerkinsH. E.BuckleyR.2013. “Online Travel Reviews as Persuasive Communication: The Effects of Content Type, Source, and Certification Logos on Consumer Behavior.” Tourism Management39:1–9.
89.
SteffelM.WilliamsE. F.2018. “Delegating Decisions: Recruiting Others to Make Choices We Might Regret.” Journal of Consumer Research44 (5): 1015–32.
90.
StraussA. L.CorbinJ. M.1990. Basics of Qualitative Research: Grounded Theory Procedures and Techniques. Thousand Oaks, CA: Sage.
91.
StraubD. W.1989. “Validating instruments in MIS research.”MIS Quarterly13 (2): 147–165.
92.
SundarS. S.WaddellT. F.JungE. H.2016. “The Hollywood Robot Syndrome Media Effects on Older Adults’ Attitudes toward Robots and Adoption Intentions.” Paper presented at: 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI).
93.
SunnyS.PatrickL.RobL.2019. “Impact of Cultural Values on Technology Acceptance and Technology Readiness.” International Journal of Hospitality Management77:89–96.
94.
TamK. Y.HoS. Y.2005. “Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective.” Information Systems Research16 (3): 271–91.
95.
ThompsonR. L.HigginsC. A.1991. “Personal Computing: Toward a Conceptual Model of Utilization.” MIS Quarterly15 (1): 125–43.
96.
Touré-TilleryM.McGillA. L.2015. “Who or What to Believe: Trust and the Differential Persuasiveness of Human and Anthropomorphized Messengers.” Journal of Marketing79 (4): 94–110.
TrevinoL. K.1992. “Experimental Approaches to Studying Ethical-Unethical Behavior in Organizations.” Business Ethics Quarterly (2): 121–36.
99.
UchyigitG.MaM.2008. Personalization Techniques and Recommender Systems. Hackensack, NJ: World Scientific.
100.
VenkateshV.MorrisM. G.AckermanP. L.2000. “A Longitudinal Field Investigation of Gender Differences in Individual Technology Adoption Decision-Making Processes.” Organizational Behavior and Human Decision Processes83 (1): 33–60.
101.
VenkateshV.MorrisM. G.DavisG. B.DavisF. D.2003. “User Acceptance of Information Technology: Toward a Unified View.” MIS Quarterly27 (3): 425–78.
102.
VenkateshV.ThongJ. Y. L.XuX.2012. “Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology.” MIS Quarterly36 (1): 157–78.
103.
WeberJ.1992. “Scenarios in Business Ethics Research: Review, Critical Assessment, and Recommendations.” Business Ethics Quarterly2 (2): 137.
104.
WilsonH. J.DaughertyP.2018. Human + Machine: Reimagining Work in the Age of AI. Boston, MA: Harvard Business Review Press.
105.
XiangZ.WangD.O’LearyJ. T.FesenmaierD. R.2015. “Adapting to the Internet: Trends in Travelers’ Use of the Web for Trip Planning.” Journal of Travel Research54 (4): 511–27.
106.
YuG.SchwartzZ.2006. “Forecasting Short Time-Series Tourism Demand with Artificial Intelligence Models.” Journal of Travel Research45 (2): 194–203.
107.
ZalamaE.Gómez-García-BermejoJ.MarcosS.DominguezS.FelizR.PinillosR.LópezJ.2014. “Sacarino, a Service Robot in a Hotel Environment.” Advances in Intelligent Systems and Computing253:3–14.
108.
ZhangK. Z. K.ZhaoS. J.CheungC. M. K.LeeM. K. O.2014. “Examining the Influence of Online Reviews on Consumers’ Decision-Making: A Heuristic–Systematic Model.” Decision Support Systems67:78–89.
109.
ZhangT.SeoS.AhnJ. A.2019. “Why Hotel Guests Go Mobile? Examining Motives of Business and Leisure Travelers.” Journal of Hospitality Marketing & Management28 (5): 621–44.
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